Mixed reality (MR) enables a novel way to visualize virtual objects on real scenarios considering physical constraints. This technology arises with other significant advances in the field of sensors fusion for human-centric 3D capturing. Recent advances for scanning the user environment, real-time visualization and 3D vision using ubiquitous systems like smartphones allow us to capture 3D data from the real world. In this paper, a disruptive application for assessing the status of indoor infrastructures is proposed. The installation and maintenance of hidden facilities such as water pipes, electrical lines and air conditioning tubes, which are usually occluded behind the wall, supposes tedious and inefficient tasks. Most of these infrastructures are digitized but they cannot be visualized onsite. In this research, we focused on the development of a new application (GEUINF) to be launched on smartphones that are capable of capturing 3D data of the real world by depth sensing. This information is relevant to determine the user position and orientation. Although previous approaches used fixed markers for this purpose, our application enables the estimation of both parameters with a centimeter accuracy without them. This novelty is possible since our method is based on a matching process between reconstructed walls of the real world and 3D planes of the replicated world in a virtual environment. Our markerless approach is based on scanning planar surfaces of the user environment and then, these are geometrically aligned with their corresponding virtual 3D entities. In a preprocessing phase, the 2D CAD geometry available from an architectural project is used to generate 3D models of an indoor building structure. In real time, these virtual elements are tracked with the real ones modeled by using ARCore library. Once the alignment between virtual and real worlds is done, the application enables the visualization, navigation and interaction with the virtual facility networks in real-time. Thus, our method may be used by private companies and public institutions responsible of the indoor facilities management and also may be integrated with other applications focused on indoor navigation.

Square markers are a widespread tool to find correspondences for camera localization because of their robustness, accuracy, and detection speed. Their identification is usually based on a binary encoding that accounts for the different rotations of the marker; however, most systems do not consider the possibility of observing reflected markers. This case is possible in environments containing mirrors or reflective surfaces, and its lack of consideration is a source of detection errors, which is contrary to the robustness expected from square markers. This is the first work in the literature that focuses on reflection-aware square marker dictionaries. We present the derivation of the inter-marker distance of a reflection-aware dictionary and propose new algorithms for generating and identifying such dictionaries. Additionally, part of the proposed method can be used to optimize preexisting dictionaries to take reflection into account. The experimentation carried out demonstrates how our proposal greatly outperforms the most popular predefined dictionaries in terms of inter-marker distance and how the optimization process significantly improves them.

Handheld LiDAR devices are revolutionizing 3D data capture, offering unprecedented accessibility and ease of use even for inexperienced users. These compact systems facilitate robust virtual reconstructions by extracting detailed geometric information from real-world environments. Advanced positioning systems in these devices generate highly accurate georeferenced 3D point clouds, enhancing the precision of scanned scenes. Leading manufacturers like FARO Technologies, Leica Geosystems, and Trimble offer diverse models, including the FARO Focus, Leica BLK360, and Trimble X7. These devices are invaluable in fields such as cultural heritage conservation, where they document and preserve historical sites; topographic mapping, providing accurate surveys in challenging terrains; and industrial inspection, ensuring thorough examinations of infrastructure and machinery. Additionally, the visualization of these 3D models on web platforms significantly enhances their accessibility and interaction. Web-based visualization tools allow users to explore, manipulate, and analyze 3D data from any location with an internet connection, democratizing access to detailed spatial information and enabling a broader range of users, from researchers to educators, to engage with complex datasets without the need for specialized software. Interactive features on these platforms, such as zooming, rotating, and measuring, provide an intuitive interface for detailed examination and collaboration. Consequently, the integration of handheld LiDAR technology with web visualization platforms opens new avenues for innovation and collaboration across various disciplines, further revolutionizing traditional methods and expanding the potential applications of 3D data capture.